Knowledge-based interpretation of architectural drawings

A method for machine interpretation of architectural (or other) schematic drawings is presented. The central problem is to build an efficient drawing parser (i.e., a program that identifies the semantic entities, characteristics, and relationships that are represented in the drawing). The parser is built from specifications of the drawing grammar and an underlying spatial model. The grammar describes what to look for, and the spatial model enables the parser to find it quickly. Coupled with existing optical recognition technology, this technique enables the use of drawings directly as: (1) a database to drive various Architecture-Engineering-Construction (AEC) applications; (2) a communication protocol to integrate CAD systems; (3) a traditional user interface.     

Flammability characteristics at applied heat flux levels up to 200 kW/m2

This paper documents the first of the two interrelated studies that were conducted to more fundamentally understand the scalability of flame heat flux, the motivation being that it has been reported that flame heat flux back to the burning surface in bench‐scale experiments is not the same as for large‐scale fires. The key aspect was the use of real scale applied heat flux up to 200kW/m² which is well beyond that typically considered in contemporary testing. The main conclusions are that decomposition kinetics needs to be included in the study of ignition and the energy balance for steady burning is too simplistic to represent the physics occurring. An unexpected non‐linear trend is observed in the typical plotting methods currently used in fire protection engineering for ignition and mass loss flux data for several materials tested and this non‐linearity is a true material response. Using measured temperature profiles in the condensed phase shows that viewing ignition as an inert material process is inaccurate at predicting the surface temperature at higher heat fluxes. The steady burning temperature profiles appear to be invariant with applied heat flux. This possible inaccuracy was investigated by obtaining the heat of gasification via the ‘typical technique’ using the mass loss flux data and comparing it to the commonly considered ‘fundamental’ value obtained from differential scanning calorimetry measurements. This comparison suggests that the ‘typical technique’ energy balance is too simplified to represent the physics occurring for any range of applied heat flux. Observed bubbling and melting phenomena provide a possible direction of study. Copyright © 2007 John Wiley & Sons, Ltd.     

Overcoming intuition: Metacognitive difficulty activates analytic reasoning.

Humans appear to reason using two processing styles: System 1 processes that are quick, intuitive, and effortless and System 2 processes that are slow, analytical, and deliberate that occasionally correct the output of System 1. Four experiments suggest that System 2 processes are activated by metacognitive experiences of difficulty or disfluency during the process of reasoning. Incidental experiences of difficulty or disfluency--receiving information in a degraded font (Experiments 1 and 4), in difficult-to-read lettering (Experiment 2), or while furrowing one's brow (Experiment 3)--reduced the impact of heuristics and defaults in judgment (Experiments 1 and 3), reduced reliance on peripheral cues in persuasion (Experiment 2), and improved syllogistic reasoning (Experiment 4). Metacognitive experiences of difficulty or disfluency appear to serve as an alarm that activates analytic forms of reasoning that assess and sometimes correct the output of more intuitive forms of reasoning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Long-term information collection with energy harvesting wireless sensors: a multi-armed bandit based approach

This paper reports on the development of a multi-agent approach to long-term information collection in networks of energy harvesting wireless sensors. In particular, we focus on developing energy management and data routing policies that adapt their behaviour according to the energy that is harvested, in order to maximise the amount of information collected given the available energy budget. In so doing, we introduce a new energy management technique, based on multi-armed bandit learning, that allows each agent to adaptively allocate its energy budget across the tasks of data sampling, receiving and transmitting. By using this approach, each agent can learn the optimal energy budget settings that give it efficient information collection in the long run. Then, we propose two novel decentralised multi-hop algorithms for data routing. The first proveably maximises the information throughput in the network, but can sometimes involve high communication cost. The second algorithm provides near-optimal performance, but with reduced computational and communication costs. Finally, we demonstrate that, by using our approaches for energy management and routing, we can achieve a 120% improvement in long-term information collection against state-of-the-art benchmarks.     

DDFSGEN

This paper presents a functional compiler for the automatic design of Direct Digital Frequency Synthesizer (DDFS) integrated circuits (ICs) using a ROM based table look-up architecture. The compiler allows the user to specify high-level specifications such as the acceptable spurious response and it generates the IC architecture, floorplan, and layout. To construct the layout for different specifications, a library of parameterized macrocells has been developed in 1.2 m CMOS technology.A test chip with a quadrature DDFS module has been generated, using the compiler, and fabricated. The chip has two input signals: one is for frequency control while the other is for phase initialization. Input and output word lengths are 16 bits and 6 bits respectively. The chip complexity is approximately 12,000 transistors (DDFS core) and the die size is 4.8×2.9mm ². A maximum sample rate of 80 MHz has been attained implying a maximum sine (cosine) output frequency of 40 MHz and a frequency resolution of 1.22 kHz. The maximum spurious level measured is –46 dB.     

The Interaction of Glymes with Surfactant Micelles

The critical micelle concentrations (CMC) values and counterion dissociation (α values) have been determined for a number of mixed micellar systems consisting of two typical ionic surfactants and glycol ethers (glymes) as cosurfactants, namely diethylene glycol dimethyl ether, diethylene glycol diethyl ether, triethylene glycol dimethyl ether, and tetraethylene glycol dimethyl ether. Conductance experiments were used to determine the CMC and α values of the mixed micelles as a function of glyme concentration in the aqueous mixed solvent. Favorable interactions between sodium dodecyl sulfate micelles and glyme cosurfactants were deduced from the decreases in the CMC values and the large increase in the α values of these systems as a function of increasing glyme concentration in the mixed solvents. In contrast to the anionic surfactant/glyme systems, in general, there appeared to be little favorable interactions between the surfactant and glymes when micelles of the cationic surfactant dodecyltrimethylammonium bromide were formed in water/glyme solvent systems containing an increasing amount of the glymes. The interaction of glymes with the surfactant micelles was examined closely via ¹³C nuclear magnetic resonance (NMR) chemical shifts for both surfactant and glyme carbons; these chemical shifts changes were interpreted in terms of the distribution and the localization of the glymes in the aggregates. Finally, partition constants, determined from two-dimensional diffusion-oriented spectroscopy (2D-DOSY) experiments, were used to calculate thermodynamic quantities of transfer of the glymes between the bulk phase and the self-assembled aggregates. All these results are interpreted in terms of the key contributions that both the glyme ethoxylated groups and alkyl endgroups make to the hydrophobic interactions.